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Paquette, Luc; Baker, Ryan S. – Interactive Learning Environments, 2019
Learning analytics research has used both knowledge engineering and machine learning methods to model student behaviors within the context of digital learning environments. In this paper, we compare these two approaches, as well as a hybrid approach combining the two types of methods. We illustrate the strengths of each approach in the context of…
Descriptors: Comparative Analysis, Student Behavior, Models, Case Studies
Rau, Martina A. – Journal of Learning Analytics, 2017
STEM instruction often uses visual representations. To benefit from these, students need to understand how representations show domain-relevant concepts. Yet, this is difficult for students. Prior research shows that physical representations (objects that students manipulate by hand) and virtual representations (objects on a computer screen that…
Descriptors: High School Students, Charter Schools, STEM Education, Knowledge Representation
Twissell, Adrian – Educational Technology & Society, 2018
Abstract electronics concepts are difficult to develop because the phenomena of interest cannot be readily observed. Visualisation skills support learning about electronics and can be applied at different levels of representation and understanding (observable, symbolic and abstract). Providing learners with opportunities to make transitions…
Descriptors: Electronics, Case Studies, Concept Formation, Scientific Concepts